FAULT LOCATION ALGORITHMS, OBSERVABILITY AND OPTIMALITY FOR POWER DISTRIBUTION SYSTEMS

Power outages usually lead to customer complaints and revenue losses. Consequently, fast and accurate fault location on electric lines is needed so that repair work can be carried out as fast as possible. Chapter 2 describes novel fault location algorithms for radial and non-radial ungrounded power distribution systems. For both types of systems, fault location approaches using line to neutral or line to line measurements are presented. It’s assumed that network structure and parameters are known, so that during-fault bus impedance matrix of the system can be derived. Functions of bus impedance matrix and available measurements at substation are formulated, from which the unknown fault location can be estimated. Evaluation studies on fault location accuracy and robustness of fault location methods to load variations and measurement errors has been performed. Most existing fault location methods rely on measurements obtained from meters installed in power systems. To get the most from a limited number of meters available, optimal meter placement methods are needed. Chapter 3 presents a novel optimal meter placement algorithm to keep the system observable in terms of fault location determination. The observability of a fault location in power systems is defined first. Then, fault location observability analysis of the whole system is performed to determine the least number of meters needed and their best locations to achieve fault location observability. Case studies on fault location observability with limited meters are presented. Optimal meter deployment results based on the studied system with equal and varying monitoring cost for meters are displayed. To enhance fault location accuracy, an optimal fault location estimator for power distribution systems with distributed generation (DG) is described in Chapter 4. Voltages and currents at locations with power generation are adopted to give the best estimation of variables including measurements, fault location and fault resistances. Chi-square test is employed to detect and identify bad measurement. Evaluation studies are carried out to validate the effectiveness of optimal fault location estimator. A set of measurements with one bad measurement is utilized to test if a bad data can be identified successfully by the presented method

A Robust Fault-Tolerant and Scalable Cluster-wide Deduplication for Shared-Nothing Storage Systems

Deduplication has been largely employed in distributed storage systems to improve space efficiency. Traditional deduplication research ignores the design specifications of shared-nothing distributed storage systems such as no central metadata bottleneck, scalability, and storage rebalancing. Further, deduplication introduces transactional changes, which are prone to errors in the event of a system failure, resulting in inconsistencies in data and deduplication metadata. In this paper, we propose a robust, fault-tolerant and scalable cluster-wide deduplication that can eliminate duplicate copies across the cluster. We design a distributed deduplication metadata shard which guarantees performance scalability while preserving the design constraints of shared- nothing storage systems. The placement of chunks and deduplication metadata is made cluster-wide based on the content fingerprint of chunks. To ensure transactional consistency and garbage identification, we employ a flag-based asynchronous consistency mechanism. We implement the proposed deduplication on Ceph. The evaluation shows high disk-space savings with minimal performance degradation as well as high robustness in the event of sudden server failure.Comment: 6 Pages including reference

Amorphous Placement and Retrieval of Sensory Data in Sparse Mobile Ad-Hoc Networks

Abstract—Personal communication devices are increasingly being equipped with sensors that are able to passively collect information from their surroundings – information that could be stored in fairly small local caches. We envision a system in which users of such devices use their collective sensing, storage, and communication resources to query the state of (possibly remote) neighborhoods. The goal of such a system is to achieve the highest query success ratio using the least communication overhead (power). We show that the use of Data Centric Storage (DCS), or directed placement, is a viable approach for achieving this goal, but only when the underlying network is well connected. Alternatively, we propose, amorphous placement, in which sensory samples are cached locally and informed exchanges of cached samples is used to diffuse the sensory data throughout the whole network. In handling queries, the local cache is searched first for potential answers. If unsuccessful, the query is forwarded to one or more direct neighbors for answers. This technique leverages node mobility and caching capabilities to avoid the multi-hop communication overhead of directed placement. Using a simplified mobility model, we provide analytical lower and upper bounds on the ability of amorphous placement to achieve uniform field coverage in one and two dimensions. We show that combining informed shuffling of cached samples upon an encounter between two nodes, with the querying of direct neighbors could lead to significant performance improvements. For instance, under realistic mobility models, our simulation experiments show that amorphous placement achieves 10% to 40% better query answering ratio at a 25% to 35% savings in consumed power over directed placement.National Science Foundation (CNS Cybertrust 0524477, CNS NeTS 0520166, CNS ITR 0205294, EIA RI 0202067

Exploring heterogeneity of unreliable machines for p2p backup

P2P architecture is a viable option for enterprise backup. In contrast to dedicated backup servers, nowadays a standard solution, making backups directly on organization's workstations should be cheaper (as existing hardware is used), more efficient (as there is no single bottleneck server) and more reliable (as the machines are geographically dispersed). We present the architecture of a p2p backup system that uses pairwise replication contracts between a data owner and a replicator. In contrast to standard p2p storage systems using directly a DHT, the contracts allow our system to optimize replicas' placement depending on a specific optimization strategy, and so to take advantage of the heterogeneity of the machines and the network. Such optimization is particularly appealing in the context of backup: replicas can be geographically dispersed, the load sent over the network can be minimized, or the optimization goal can be to minimize the backup/restore time. However, managing the contracts, keeping them consistent and adjusting them in response to dynamically changing environment is challenging. We built a scientific prototype and ran the experiments on 150 workstations in the university's computer laboratories and, separately, on 50 PlanetLab nodes. We found out that the main factor affecting the quality of the system is the availability of the machines. Yet, our main conclusion is that it is possible to build an efficient and reliable backup system on highly unreliable machines (our computers had just 13% average availability)